Homework11
Sophie Kogut
4/8/2020
Batch Processing
- Repeat the exercise from the Batch Processing Lecture (7th April), but do it using real data sets rather than purely simulated. Check with folks in your lab to see if there are multiple data sets available for analysis. Stick to simple data analyses and graphics, but try to set it up as a batch process that will work on multiple files and save summary results to a common file. If you can only find a data set, then simulate a couple of others by following the methods in Homework #6 by selecting appropriate statistical distributions and estimating parameters for those from the real data.
Hopefully, this exercise will contribute to some actual work that you are trying to do in your research!
# Batch processing to create graphs for SelectPos
# load data ----------------------------------
library(ggplot2)
library(data.table)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:data.table':
##
## between, first, last## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionload("/Users/skogut/Desktop/Thesis/SelectPosVACC.rda")
SelectPos<- arrange(SelectPos, by= desc(Slope))
SelectPos$ERV<- gsub("X", "", SelectPos$ERV)
SelectPairs<- SelectPos[1:1000, 1:2]
SelectPairs$ERV<- gsub("\\.", "-", SelectPairs$ERV)
print(SelectPairs)## ERV Transcript
## 1 727 ENST00000361381.2
## 2 727 ENST00000361453.3
## 3 K-32 ENST00000387347.2
## 4 727 ENST00000361567.2
## 5 2758 ENST00000361453.3
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## 8 727 ENST00000361335.1
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## 10 2758 ENST00000387347.2
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## 999 UID-51 ENST00000361681.2
## 1000 2201 ENST00000369151.7# Transcripts<- fread("/Users/skogut/Desktop/Thesis/Transcripts_normalized_counts_WF.csv")
# ERV<- fread("/Users/skogut/Desktop/Thesis/ERV_normalized_counts_WF.csv")
Transcripts<- readRDS("Transcripts.RDS")
ERV<- readRDS("ERV.RDS")
# saveRDS(Transcripts, "Transcripts.RDS")
# saveRDS(ERV, "ERV.RDS")
dir.create("PositiveERV_Trans/")## Warning in dir.create("PositiveERV_Trans/"): 'PositiveERV_Trans' already exists# Create files ----------------------------------
# two sets of counts per file: 1 set from ERV, transcript per top 1000 pairs
########################################################
# FUNCTION file_builder
# description: creates a sest of random files for regression
# inputs: file_n = number f files to create
# file_folder = name of folder for random file
# file_size = c(min,max) number of rows in file
# file_NA= average number of NA values per column
# outputs: creates a set of random files
# -----------------------------------------------------
file_builder <- function(file_n=1000,
file_folder= "PositiveERV_Trans/",
ERVdata= 1:1000,
Transcriptdata= 1:1000,
SelectPairs= 1:1000) {
for (i in 1:nrow(SelectPairs)) {
var_x<- SelectPairs[i,1] # ERV
var_y<-SelectPairs[i,2] # Transcript
df<- data.frame(var_x = ERVdata[[ which(colnames(ERVdata)== var_x)]], var_y= Transcriptdata[[which(colnames(Transcriptdata)== var_y)]]) # bind into a data frame
colnames(df)<- c(var_x, var_y)
print(df)
# create label for file name with padded zeroes
file_label<- paste(file_folder, "PairFile",
formatC(i,
width=3,
format= "d",
flag= "0"),
".csv",
sep="")
# set up data file and incorporate time stamp and minimal meta data
write.table(cat("# Simulated random data filefor batch processing", "\n",
"# timestamp: ", as.character(Sys.time()),
"\n",
"# SEK", "\n",
"#----------------------------", "\n",
"\n",
file=file_label,
row.names= "",
col.names= "",
sep= "") )
# now add the data frame
write.table(x=df,
file= file_label,
sep=",",
row.names= FALSE,
append=TRUE)
}
} # end of file_builder
########################################################
# Create regression function/ graphing function ----------------------------------
########################################################
# FUNCTION reg_stats
# description: fits liner model extract m stats
# inputs: 2column data frame (x and y)
# outputs: slope, p-value, and r2
# -----------------------------------------------------
reg_stats <- function(d= NULL) {
if( is.null(d)){
x_var<- runif(10)
y_var<- runif(10)
d<- data.frame(x_var, y_var) }
.<- lm(data=d, d[,2]~d[,1])
.<- summary(.)
stats_list<- list(Slope=.$coefficients[2,1],
pval= .$coefficients[2,4],
r2=.$r.squared)
return(stats_list)
} # end of reg_stats
########################################################
# test
#######################################################
#global
file_folder<- "PositiveERV_Trans/"
n_files<- 100
file_out<- "StatsSummaryHW.csv"
file_names<- list.files(path= file_folder)
######################################################## running file builder to build files
file_builder(ERVdata = ERV, Transcriptdata = Transcripts, SelectPairs = SelectPairs)# batch process by looping through individual files ----------------------------------
# create data frame to hold summary stats
ID<- seq_along(file_names)
file_name<- file_names
slope<- rep(NA, length(file_names))
pval<- rep(NA, length(file_names))
r2<- rep(NA, length(file_names))
stats_out<- data.frame(ID, file_name, slope, pval, r2)
# batch process by looping through individual files
for(i in seq_along(file_names)) {
data<- read.table(file=paste(file_folder, file_names[i],
sep=""),
sep=",",
header= TRUE)
.<- reg_stats(d=data) # pull out regression stats from clean file
stats_out[i,3:5]<- unlist(.) # unlist, copy into last three cols
}
# set up an output file and incorporate time stamp and minimal metadata
write.table(cat( "# Summary stats for",
"batch processing of regression models",
"\n",
"# timestamp: ", as.character(Sys.time()),
"\n",
file= file_out,
row.names= "",
col.names="",
sep= ""))## ""# set up an output file and incorporate time stamp and minimal metadata
# now add the data frame
write.table(x=stats_out,
file=file_out,
row.names=FALSE,
col.names=TRUE,
sep= ",",
append=TRUE)## Warning in write.table(x = stats_out, file = file_out, row.names = FALSE, :
## appending column names to filefile_out<- "StatsSummaryHW.csv"
# arranging data to find something meaningful
stats_out<- arrange(stats_out, desc(r2))
head(stats_out)## ID file_name slope pval r2
## 1 950 PairFile949.csv 842.8526 2.313595e-52 0.9844926
## 2 824 PairFile823.csv 897.8977 1.133303e-27 0.8821019
## 3 579 PairFile578.csv 1266.0763 1.569202e-27 0.8807268
## 4 976 PairFile975.csv 789.6071 2.540270e-27 0.8786620
## 5 796 PairFile795.csv 924.5246 5.063990e-27 0.8756426
## 6 999 PairFile998.csv 777.0859 9.411610e-27 0.8728661# plotting quick scatterplots to look for outliers, in the top 50 pairs when ordered by r2
for (i in 1:50) {
data<- read.table(file=paste(file_folder, stats_out$file_name[i],
sep=""),
sep=",",
header= TRUE)
p<- qplot(x=data[,1],
y=data[,2],
geom= c("smooth", "point"), method= "lm",
xlim= c(0, 25),
ylim= c(0,10000))
print(i)
print(p)
Sys.sleep(1.5)
}## Warning: Ignoring unknown parameters: method## [1] 1## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning -
## Inf## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 2## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 3## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 4## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 5## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 6## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 7## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 8## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 34 rows containing non-finite values (stat_smooth).## Warning: Removed 34 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 9## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 10## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 11## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 44 rows containing non-finite values (stat_smooth).## Warning: Removed 44 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 12## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning -
## Inf## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 13## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 8 rows containing missing values (geom_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 14## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 18 rows containing missing values (geom_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 15## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 16## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 37 rows containing missing values (geom_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 17## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 19 rows containing missing values (geom_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 18## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 40 rows containing missing values (geom_smooth).## Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning -
## Inf## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 19## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 20## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 28 rows containing missing values (geom_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 21## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 2 rows containing non-finite values (stat_smooth).## Warning: Removed 2 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 22## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 23## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 24## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 39 rows containing non-finite values (stat_smooth).## Warning: Removed 2 rows containing missing values (geom_smooth).## Warning: Removed 39 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 25## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 10 rows containing non-finite values (stat_smooth).## Warning: Removed 10 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 26## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 41 rows containing missing values (geom_smooth).## Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning -
## Inf## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 27## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 33 rows containing missing values (geom_smooth).## Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning -
## Inf## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 28## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 35 rows containing non-finite values (stat_smooth).## Warning: Removed 35 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 29## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 15 rows containing non-finite values (stat_smooth).## Warning: Removed 15 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 30## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 3 rows containing non-finite values (stat_smooth).## Warning: Removed 3 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 31## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning -
## Inf## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 32## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 34 rows containing non-finite values (stat_smooth).## Warning: Removed 34 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 33## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 22 rows containing non-finite values (stat_smooth).## Warning: Removed 22 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 34## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 35## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 11 rows containing non-finite values (stat_smooth).## Warning: Removed 11 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 36## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 53 rows containing non-finite values (stat_smooth).## Warning: Removed 53 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 37## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 8 rows containing non-finite values (stat_smooth).## Warning: Removed 8 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 38## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 8 rows containing non-finite values (stat_smooth).## Warning: Removed 8 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 39## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 10 rows containing non-finite values (stat_smooth).## Warning: Removed 10 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 40## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 45 rows containing non-finite values (stat_smooth).## Warning: Removed 45 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 41## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 44 rows containing non-finite values (stat_smooth).## Warning: Removed 44 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 42## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 43## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 7 rows containing non-finite values (stat_smooth).## Warning: Removed 7 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 44## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 7 rows containing non-finite values (stat_smooth).## Warning: Removed 7 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 45## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 58 rows containing non-finite values (stat_smooth).## Warning: Removed 58 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 46## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 58 rows containing non-finite values (stat_smooth).## Warning: Removed 58 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 47## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 34 rows containing non-finite values (stat_smooth).## Warning: Removed 34 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 48## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 11 rows containing non-finite values (stat_smooth).## Warning: Removed 11 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 49## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 52 rows containing non-finite values (stat_smooth).## Warning: Removed 52 rows containing missing values (geom_point).## Warning: Ignoring unknown parameters: method
## [1] 50## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 58 rows containing non-finite values (stat_smooth).## Warning: Removed 58 rows containing missing values (geom_point).